• Characterisation of demoulding parameters in micro-injection moulding

      Griffiths, C.A.; Tosello, G.; Dimov, S.S.; Scholz, S.G.; Rees, A.; Whiteside, Benjamin R. (2015-08)
      Condition monitoring of micro injection moulding is an effective way of understanding the processing effects of variable parameter settings. This paper reports an experimental study that investigates the characteristics of the demoulding behaviour in micro injection moulding (A mu-IM) with a focus on the process factors that affect parts' quality. Using a Cyclic Olefin Copolyme (COC) microfluidics demonstrator, the demoulding performance was studied as a function of four process parameters (melt temperature, mould temperature, holding pressure and injection speed), employing the design of experiment approach. The results provide empirical evidences on the effect that processing parameters have on demoulding conditions in A mu-IM, and identifies combinations of parameters that can be used to achieve the optimal processing conditions in regards to demoulding behaviour of micro parts. It was concluded that there was a direct correlation between the applied pressure during part filling, holding phases and the demoulding characteristic factors of the A mu-IM cycle such as ejection force, integral and time.
    • Correlating nano-scale surface replication accuracy and cavity temperature in micro-injection moulding using in-line process control and high-speed thermal imaging

      Baruffi, F.; Gülçür, Mert; Calaon, M.; Romano, J.-M.; Penchev, P.; Dimov, S.; Whiteside, Benjamin R.; Tosello, G. (2019-11)
      Micro-injection moulding (μIM) stands out as preferable technology to enable the mass production of polymeric components with micro- and nano-structured surfaces. One of the major challenges of these processes is related to the quality assurance of the manufactured surfaces: the time needed to perform accurate 3D surface acquisitions is typically much longer than a single moulding cycle, thus making impossible to integrate in-line measurements in the process chain. In this work, the authors proposed a novel solution to this problem by defining a process monitoring strategy aiming at linking sensitive in-line monitored process variables with the replication quality. A nano-structured surface for antibacterial applications was manufactured on a metal insert by laser structuring and replicated using two different polymers, polyoxymethylene (POM) and polycarbonate (PC). The replication accuracy was determined using a laser scanning confocal microscope and its dependence on the variation of the main μIM parameters was studied using a Design of Experiments (DoE) experimental approach. During each process cycle, the temperature distribution of the polymer inside the cavity was measured using a high-speed infrared camera by means of a sapphire window mounted in the movable plate of the mould. The temperature measurements showed a high level of correlation with the replication performance of the μIM process, thus providing a fast and effective way to control the quality of the moulded surfaces in-line.